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Understanding time is crucial for understanding events expressed in naturallanguage. Because people rarely say the obvious, it is often necessary to havecommonsense knowledge about various temporal aspects of events, such asduration, frequency, and temporal order. However, this important problem has sofar received limited attention. This paper systematically studies this temporalcommonsense problem. Specifically, we define five classes of temporalcommonsense, and use crowdsourcing to develop a new dataset, MCTACO, thatserves as a test set for this task. We find that the best current methods usedon MCTACO are still far behind human performance, by about 20%, and discussseveral directions for improvement. We hope that the new dataset and our studyhere can foster more future research on this topic.

"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding